Modeling Domains as Distributions with Uncertainty for Cross-Domain Recommendation
Author:
Affiliation:
1. Shenzhen International Graduate School, Tsinghua University, Shenzhen, China
2. Xiaohongshu Inc., Shanghai, China
Funder
The Special Projects in Key Fields from the Department of Education of Guangdong Province
Guangdong Provincial Key R&D Program
Dongguan Science and Technology of Social Development Program
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3626772.3657930
Reference30 articles.
1. Martin Arjovsky, Soumith Chintala, and Léon Bottou. 2017. Wasserstein generative adversarial networks. In International conference on machine learning. PMLR, 214--223.
2. Cross-Domain Recommendation to Cold-Start Users via Variational Information Bottleneck
3. Wide & Deep Learning for Recommender Systems
4. An elementary proof of the triangle inequality for the Wasserstein metric
5. Ignacio Fernández-Tob'ias, Iván Cantador, Marius Kaminskas, and Francesco Ricci. 2012. Cross-domain recommender systems: A survey of the state of the art. In Spanish conference on information retrieval, Vol. 24. sn.
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